ROLE OF ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN SUPPLY CHAIN AND LOGISTICS IN TRANSITION TOWARDS A CIRCULAR ECONOMY

Abstract

This literature review examines the transformative impact of artificial intelligence (AI) on facilitating the transition of supply chain and logistics systems toward a circular economy (CE). Drawing on a synthesis of recent empirical and conceptual studies, the review identifies key Al technologies, including machine learning, deep learning, natural language processing, and Internet of Things (IoT) devices, and their applications across various CE practices, such as reverse logistics, waste minimisation, green procurement, and ethical sourcing. The findings indicate that Al significantly enhances operational efficiency, predictive capabilities, and resource optimisation, while also addressing environmental challenges through improved transparency and automation. Furthermore, the review highlights how the integration of Al with IoT and blockchain technologies enhances material traceability and emission tracking, thereby supporting the design of circular supply networks. Despite these advancements, notable challenges persist, including data silos, high infrastructure costs, and ethical concerns regarding the collaboration between humans and Al. The review also reveals a regional research gap, with limited localised models for developing economies like Sri Lanka. Conclusively, the study calls for multi-stakeholder collaboration, improved regulatory frameworks, and empirical validations to harness Al's full potential in achieving sustainable and circular logistics systems.